Victims of identity
theft in 2017 (Javelin)
Median cost of fraud related
incidents (Consumer Sentinel Network)
Losses from identity theft in
2017 (Javelin)
Revealing humans who act like machines. Our machine learning detects anomalous behavior (form familiarity, creation speed…) combined with other device information to uncover human farms and mitigate them.
No more accounts from bots. Our powerful bot-detection algorithm identifies a wide range of attacks, including sophisticated scripts that mimic human input and pauses.
Detecting threats among brand-new users. The model uses powerful machine learning fed billions of cross-client parameters and data sets. It identifies behavior without the need to recognize a user or learn from your specific traffic.
You can control the performance of NuDetect for OAO by adjusting the configurations. This flexibility allows you to decide if you want to want to catch more of less fraud depending on your false positive goal. An aggressive goal can detect around 70% of fraud and deliver under a 1% false positive rate.
Weed out traffic you don’t want. Whether a script, human farm, or someone with a lot of free time, mitigate fraudulent accounts that bypass bot-detection tools.
Find fraudulent applications before they are submitted. Our real-time intelligence gives a score before you process that application, allowing you to block it or give it a closer look.
Tackle fraud at its root. By mitigating an application before it’s submitted you are also mitigating future fraud losses, brand damage, and customer churn.
You don’t need to wear many hats. By automatically weeding out fraudulent accounts you and your team will reduce manual reviews and have more time to focus on what you are good at: your business.
Large U.S. bank
“We are finding out about fraudulent applications too late; once they use the credit and leave it unpaid, but our bot manager can’t detect it.”